While deep learning (DL) offers the compelling ability to detect details beyond human vision, its black-box nature makes it prone to misinterpretation. A key problem is algorithmic shortcutting, where DL models inform their predictions with patterns ...
MedSegBench is a comprehensive benchmark designed to evaluate deep learning models for medical image segmentation across a wide range of modalities. It covers a wide range of modalities, including 35 datasets with over 60,000 images from ultrasound, ...
Sea turtles exhibit high migratory rates and occupy a broad range of habitats, which in turn makes monitoring these taxa challenging. Applying deep learning (DL) models to vast image datasets collected from citizen science programs can offer promisin...
Skin lesion segmentation plays a pivotal role in the diagnosis and treatment of skin diseases. By using deep neural networks to segment lesion areas, doctors can more accurately assess the severity of health-related conditions of patients and promptl...
Deep learning shows promise for medical image segmentation but suffers performance declines when applied to diverse healthcare sites due to data discrepancies among the different sites. Translating deep learning models to new clinical environments is...
Neural networks : the official journal of the International Neural Network Society
Nov 23, 2024
Medical image segmentation is essential for accurately representing tissues and organs in scans, improving diagnosis, guiding treatment, enabling quantitative analysis, and advancing AI-assisted healthcare. Organs and lesion areas in medical images h...
OBJECTIVE: Deep learning approaches such as DeepACSA enable automated segmentation of muscle ultrasound cross-sectional area (CSA). Although they provide fast and accurate results, most are developed using data from healthy populations. The changes i...
Examining the relationship between streetscape features and road traffic crashes is vital for enhancing roadway safety. Traditional field surveys are often inefficient and lack comprehensive spatial coverage. Leveraging street view images (SVIs) and ...
The global burden of infectious diseases significantly affects mortality rates, with their varying symptoms making it challenging to assess and determine the severity of infections. Different countries face unique challenges related to these diseases...
Accurate polyp image segmentation is of great significance, because it can help in the detection of polyps. Convolutional neural network (CNN) is a common automatic segmentation method, but its main disadvantage is the long training time. Transformer...
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